Uncertainty-Flexibility Matching Engine For Inter-Temporal Electric Energy Products

ABSTRACT

Exemplary embodiments relate to a matching engine for the coordination of electric energy production and consumption, in particular in the presence of uncertainty. The engine provides matching based on uncertainty and flexibility in the electric supply and demand chains. The system can use quantified characterizations of uncertainty and flexibility provided by performance measurements of the elements in the chain.

FIELD OF TECHNOLOGY

The present invention relates to electric power grids and electricenergy production and consumption systems in the presence ofuncertainty. In particular, the present invention relates tosensor-controlled electric energy production and demand.

BACKGROUND OF THE INVENTION

Electric power grids face several challenges. Variability anduncertainty in demand and supply can create a mismatch that causes aloss of efficiency, system failures, and wasted resources. This mismatchcan arise from the variability and uncertainty that exists in presentrenewable energy production and in consumer demand. For example, solarand wind power generation are both weather dependent. While predictionscan be made, there still remains a significant amount of uncertainty. Onthe other side, energy demand is also not fully known ahead of time asheating and cooling loads, for instance, are affected by weather orother events. As the share of renewable energy in the power grid grows,total energy generation and consumption become less predictable.

Furthermore, current trends point to an increase in decentralizedproduction. Electricity generation may become more distributed andenergy may be produced in smaller amounts at each generating unit.Consumers and businesses may add more solar panels at or near theirpoint of use. In addition, power companies may add smaller, fastreacting, gas-powered turbines to react to fluctuating demand, and theseturbines may be placed in distributed locations throughout the grid tohelp with demand.

Because the electric power grid can neither store, nor absorb orgenerate electric energy, a continuous balance between energy in- andoutflow is required for reliable and safe operation. Without properbalancing, there can be a lack of energy supply at one time, or anoversupply at other time, leading to undesired deviations from nominalgrid frequency and voltage, to grid congestion, and damage to powersystem equipment.

In the current electricity markets, only products to hedge againstuncertainty of price, such as options and futures, exist. There arecurrently no products known that incorporate uncertainty of volume.Thus, no known products address the changes in supply of and demand forelectricity.

Current methods for addressing these issues rely on grid-reinforcement,demand-response, and multi-stage markets. Grid-reinforcement includesupgrading transformers and power cables. However, while these measuresare reliable they require additional infrastructure and, thus, areexceedingly costly and time-consuming. Demand-response programs, such asproviding variable energy pricing, are simple, cheap, and distributedbut are unreliable as the price elasticity of the energy consumers isunknown. Multi-stage electric energy and power markets are a knownsolution that is reliable. However, these approaches only work forcontrollable generation, are complex, have limited offerings, and areonly available to transmission system operators. Furthermore,demand-response and multi-stage markets are reactive and unable toaddress problems until they occur.

There exist flexibility market prototypes such as iPower, PowerMatcher,and UFLEX. However, many of these market prototypes allow onlyrestrictive flexibility products and do not consider inter-temporalconstraints.

What is needed is a system that can match uncertainty with flexibility.

SUMMARY OF INVENTION

According to exemplary embodiments existing markets are extended byproviding a single market for electric energy and power products. Thesystem matches uncertainty by flexibility ahead of time and, thus, canproactively hedge against uncertainty by reserving a sufficient amountof flexibility. Furthermore, the system exploits the fact that manysystems feature energetic flexibility, which has been traditionallyignored. In contrast to contemporary reserve markets for transmissionsystem operators, the proposed system is open to anyone wishing to hedgetheir uncertainty by flexibility. Moreover, additional marketparticipants can be brought in, as many types of small-scale distributedsystems, such as heating and cooling systems and plug-in electricvehicles, feature some energetic flexibility. The system uses aquantitative description of flexibility and uncertainty and allows forproducts to trade flexibility and uncertainty including inter-temporalconstraints.

In an embodiment, a smart grid energy system comprises a matching engineoperatively connected to the at least one electric energy generator andthe at least one electric load over a computer communication network andprogrammed to receive, over the computer communication network, aquantitative measure of uncertainty from the generator, where thegenerator comprises an uncertain rate of energy generation, receive,over the computer communication network, a quantitative measure offlexibility from the electric load, where the load comprises a flexiblerate of energy consumption, generate a time-dependent control signalwhere the control signal is based on a zonotope mapping using thequantitative measure of uncertainty and the quantitative measure offlexibility, and transmit the time-dependent control signal to the loadto modify rate of energy consumption.

In a further embodiment, a method of matching uncertainty in energyproduction and/or consumption with flexibility in energy productionand/or consumption comprises receiving at least one flexibility offerfrom at least one flexible energy unit, where the flexible energy unitis configured to generate and/or consume electric energy, receiving atleast one flexibility request from at least one uncertain energy unit,where the uncertain energy unit is configured to generate and/or consumeelectric energy, clearing the at least one flexibility offer and atleast one flexibility request, performing an assignment of potentialrealizations of the uncertain electricity generation and/or consumptionto corresponding control signals for the electric energy generationand/or consumption of the at least one flexible energy unit, receivingat least one electric energy measurement for a first at least oneinterval of a delivery period from the at least one uncertain energyunit, and transmitting at least one control signal value for a second atleast one time interval of the delivery period to the at least oneflexible energy unit based on the assignment.

Numerous other embodiments are described throughout herein. All of theseembodiments are intended to be within the scope of the invention hereindisclosed. Although various embodiments are described herein, it is tobe understood that not necessarily all objects, advantages, features orconcepts need to be achieved in accordance with any particularembodiment. Thus, for example, those skilled in the art will recognizethat the invention may be embodied or carried out in a manner thatachieves or optimizes one advantage or group of advantages as taught orsuggested herein without necessarily achieving other objects oradvantages as may be taught or suggested herein.

The methods and systems disclosed herein may be implemented in any meansfor achieving various aspects, and may be executed in a form of amachine-readable medium embodying a set of instructions that, whenexecuted by a machine, cause the machine to perform any of theoperations disclosed herein. These and other features, aspects, andadvantages of the present invention will become readily apparent tothose skilled in the art and understood with reference to the followingdescription, appended claims, and accompanying figures, the inventionnot being limited to any particular disclosed embodiment(s).

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentinvention can be understood in detail, a more particular description ofthe invention, briefly summarized above, may be had by reference toembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate onlytypical embodiments of this invention and the invention may admit toother equally effective embodiments.

FIG. 1A illustrates a system diagram of the matching engine and theelectric energy systems connected to it; according to an embodiment ofthe present invention; and FIG. 1B is a simplified block diagram of anexample apparatus in accordance with exemplary embodiments.

FIG. 2A illustrates a probability density plot of the uncertainty thatan electric energy system might expect for a given future time interval,according to an embodiment of the present invention.

FIG. 2B illustrates the set of feasible discrete-time power trajectoriesthat a flexible system can follow, according to an embodiment of thepresent invention.

FIG. 3A illustrates how the expected uncertainty of a unit isouter-approximated by a zonotopic set, according to an embodiment of thepresent invention.

FIG. 3B illustrates how the feasible set available from a flexible unitis inner-approximated by a zonotopic set, according to an embodiment ofthe present invention.

FIG. 4 illustrates a process flow for a clearing procedure, according toan embodiment of the present invention.

FIG. 5 illustrates a process timeline, according to an embodiment of thepresent invention.

Other features of the present embodiments will be apparent from theDetailed Description that follows.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In the following detailed description of the preferred embodiments,reference is made to the accompanying drawings, which form a parthereof, and within which are shown by way of illustration specificembodiments by which the invention may be practiced. It is to beunderstood that other embodiments may be utilized and structural changesmay be made without departing from the scope of the invention.Electrical, mechanical, logical and structural changes may be made tothe embodiments without departing from the spirit and scope of thepresent teachings. The following detailed description is therefore notto be taken in a limiting sense, and the scope of the present disclosureis defined by the appended claims and their equivalents.

The system, in an embodiment provides compensation of uncertainty inelectric energy generation and/or consumption with flexibility inelectric energy generation and/or consumption. On the one hand,renewable energy sources such as solar and wind power plants are subjectto significant uncertainty. Their exact power generation is unknownahead of time and controllable only to some extent. On the other hand,many existing electric energy systems are flexible in their electricenergy generation and/or consumption. For example, thermal power systemscan adjust their output. HVAC systems have thermal energy buffers thatallow deferral of consumption. Batteries and plug-in electric vehicleshave chemical energy batteries that can act as buffers to shiftdemand/supply. Hydro storage power stations create potential energybuffers from pumping water in reservoirs. However, in order to use theenergetic flexibility available, a quantitative description thereof isrequired.

As used herein, the energetic ‘flexibility’ refers to the ability of asystem to adjust the volume and/or timing of its electric energy intakefrom or its energy output to the power grid. A buyer of a flexibilityoffer has the right, but not the obligation, to ask from the seller ofthe flexibility offer to implement any electric power trajectory in theflexible set specified in the offer. The seller of the flexibility offerhas the corresponding obligation to implement any electric powertrajectory asked for by the buyer. In this sense, a flexibility offerresembles a financial option. However, the big difference is that aflexibility offer is an option with regard to the volume of thecommodity traded (electric power/energy) and not with regard to theprice.

According to an example embodiment, both energetic uncertainty andenergetic flexibility of systems are captured by zonotopic sets. Thereasons for choosing zonotopes and their advantages are described below.

An example embodiment is able to match uncertainty by flexibility andthereby able to compensate for any realization of the uncertainty. Thesystem comprises an uncertainty-flexibility matching engine that matchesflexibility offers and requests, collects and handles information andcontracting, sends out confirmation, activation and control signals,verifies appropriate delivery of traded products, and executes all theaccounting/billing.

FIG. 1 illustrates a block diagram of an example system 100, inaccordance with exemplary embodiments. In the example shown in FIG. 1,the system 100 includes an uncertainty-flexibility matching engine 110that is connected via a communication network to uncertain systems 120,such as energy systems having energy resources that are subjected tosome degree of uncertainty. The matching engine 110 may also beconnected to flexible systems 130, such as electric energy systems whoseenergy generation and/or consumption is to some degree flexible. Thematching engine 110 may then match flexibility requests 121 andflexibility offers 131. This allows electric energy generation orconsumption units 120, 130 to trade electric energy and power and toproactively hedge against expected uncertainty ahead of time.

One or more uncertain systems 120 may, for example, submit theflexibility requests 121 for a predefined time of delivery to thematching engine 110. A flexibility request 121 for a given time intervalmay include i) a quantitative description of the uncertainty in electricenergy generation and/or consumption to be compensated by flexibility,and ii) the maximum price the owner of the uncertain system 120 iswilling to pay for flexibility. The uncertainty sets may be captured byzonotopes. Alternatively, the one or more uncertain systems 120 maysubmit historic electric energy measurements or a probability densityestimate of the uncertainty together with a confidence level and amaximum price. Based on this information, the matching engine 110 cangenerate the corresponding zonotopic flexibility request. The one ormore uncertain systems 120 may include, for example, wind turbinegenerators, solar power generators, or other power producers orconsumers subject to uncertainty.

One or more flexible systems 130 may submit flexibility offers 131 tothe matching engine 110. Flexible systems 130 may include, for example,electric vehicle chargers, electric heaters, or other power producers orconsumers having flexibility. A flexibility offer 131 for a given timeinterval may include i) a quantitative description of the energeticflexibility the unit can provide, and ii) a cost function that assignsminimum prices to any subset of the flexibility submitted. Theflexibility sets may be captured by zonotopes. Alternatively, one ormore flexible systems 130 may subscribe to a flexibility identificationprogram. In this case, the flexible system 130 provides, for example,electric energy measurements to the matching engine 110 over apredefined time duration. In addition, the flexible system may receivecontrol signals 112 from the matching engine 110. For example, a controlsignal may include one or more timed reference power values that may beused by the flexible unit to determine its electricity consumption orgeneration. This way, the flexibility of the flexible system 130 may beidentified autonomously (e.g. without user interaction) and appropriatefuture flexibility offers 131 can be generated upon request. Similar toexisting electricity markets, in some embodiments the matching engine110 may accept flexibility requests 121 and flexibility offers 131 for aparticular time of delivery up to a certain submission deadline. Afterthis deadline, the matching engine 110 matches the flexibility requests121 and flexibility offers 131 in an economically optimal way based onthe potential realizations. Details of the matching procedure arediscussed in more detail below. After the matching has finished, theuncertain systems 120 are sent a notification 111 of whether or nottheir flexibility requests 121 have been matched. Similarly, flexiblesystems 130 are sent a notification 112 indicating, for example, whethertheir entire flexibility, subsets thereof, or none of their flexibilityhas been matched. The matching engine 110 keeps track of the foundmatching and sets up corresponding contracts between sellers and buyersof flexibility. During time of delivery, the uncertain systems 120provide electric energy measurements to the matching engine 110, and thematching engine 110 translates them into control signals 112 assigned tocontracted flexible systems 130. A detailed description of theinformation flow before and after the matching procedure, as well asduring time of delivery and for ex-post accounting, is given below.

Referring now to FIG. 1B, this figures illustrates a simplified blockdiagram of various electronic devices and apparatuses that are suitablefor use in practicing the exemplary embodiments described herein. Forexample, one or more of systems 120, 130, and 110 may comprise computer140. The computer 140 includes a controller, such as a computer or adata processor(s) 150 and a computer-readable memory or medium embodiedas a memory(ies) 155 that stores a program of computer instructions(PROG) 190.

The PROG 190 includes program instructions that, when executed by theassociated processor(s) 150, enable the various electronic devices andapparatuses to operate in accordance with exemplary embodiments. Thatis, various exemplary embodiments may be implemented at least in part bycomputer software executable by the processors 150 of the computer 140,or by hardware, or by a combination of software and hardware (andfirmware).

The memory(ies) 155 may be of any type suitable to the local technicalenvironment and may be implemented using any suitable data storagetechnology, such as semiconductor based memory devices, flash memory,magnetic memory devices and systems, optical memory devices and systems,fixed memory, and removable memory. The processor(s) 150 may be of anytype suitable to the local technical environment, and may include one ormore of general purpose computers, special purpose computers,microprocessors, digital signal processors (DSPs), and processors basedon a multicore processor architecture, as non-limiting examples.

In this example, the computer 140 also comprises one or more network(N/W) interfaces (I/F(s)) 118, interface circuitry 178, and may includeor be connected to interface elements 173. A server, depending onimplementation, may only be accessed remotely (e.g., via a N/W IF 118),and as such would not use the interface elements 173, which couldinclude a display, keyboard, mouse, and the like. It is also noted thata “computer system” as this term is used herein may include multipleprocessors and memories, e.g., in a cloud-based system.

The NW I/F(s) 118 may be wired and/or wireless and communicate over theInternet/other network(s) via any communication technique. In thisexample, the NW I/F(s) 118 comprise one or more transmitters 118-1, andone or more receivers 118-2. Such transmitters 118-1 and receivers 118-2can be wireless radio frequency (RF) transmitters or receiverssupporting, e.g., cellular or local or wide area network frequencies andprotocols. The transmitters or receivers may also be wired and supportwired protocols such as USB (universal serial bus), networks such asEthernet, and the like. There may also be a combination of theseprotocols used.

FIG. 2A illustrates a probability density plot 210 of the uncertaintythat a system might expect with regard to power consumption orgeneration, according to an example embodiment. Shown are only the firsttwo time steps of a discrete-time planning horizon that can comprise anarbitrary finite number of time steps. FIG. 2B illustrates the set offeasible power trajectories a system can follow during a given planninghorizon, according to an embodiment of the present invention. Shown areonly the first two time steps of a discrete-time planning horizon thatcan comprise an arbitrary finite number of time steps. This set is alsoreferred to as the feasible set 220. Feasible sets are defined by allthe constraints imposed on a power trajectory. Common types ofconstraints are constraints on power, energy, or power ramp rates.

FIG. 3A illustrates how a certain mass of the probability density 310modeling the uncertainty is captured within a zonotopic set 320,according to an embodiment of the present invention. If the systemsubjected to this uncertainty wishes to hedge against this amount ofuncertainty, it may submit the zonotope 320 as a flexibility request tothe matching engine. FIG. 3B illustrates how a feasible set 330 of aflexible system is inner-approximated by a zonotopic set 340, accordingto an embodiment of the present invention. The flexible system can thensubmit the zonotope 340 as a flexibility offer to the matching engine.In FIG. 3A and FIG. 3B, the approach of this disclosure is used todescribe both uncertainty and flexibility by zonotopes. Theuncertainty-flexibility matching engine can be used to check if theflexibility request shown in FIG. 3A can be matched by the flexibilityoffer in FIG. 3B. In the case shown here, the uncertainty zonotope 320can be matched with the flexibility zonotope 340 available because theflexibility zonotope fully covers the uncertainty zonotope.

FIG. 4 illustrates a process flow 400 for a clearing procedure,according to an embodiment of the present invention. Flexibility offers410 and flexibility requests 480 are submitted to an ordered pool 420 offlexibility offers and requests. The clearing procedure goes through thelist of flexibility requests 480 and checks whether or not they can bematched by one or a combination of multiple flexibility offers 410. Theclearing procedure is a two-step approach: First, matching with regardto deviations from baselines is checked 430. This corresponds toclearing a regulation power market. However, products withinter-temporal constraints, such as constraints on energy or power ramprates, can be included. Successful matching in this first step 430 is anecessary condition for clearing a flexibility request. Thus, ifmatching is not possible, the request is rejected 440. Second, matchingwith regard to baselines is checked 450. This corresponds to clearingtraditional electric energy markets. If and only if a matching ispossible in deviations 440 and baselines 460, the flexibility request ismatched successfully. A notification of acceptance is sent to the buyer480 of flexibility offer and the matched flexibility offers and requestsare removed from the flexibility pool 420. Contracts 470 are set upbetween the buyer 480 and one or many providers 410 of flexibilityoffers.

In embodiments, the process flow for clearing the flexibility offers andrequests may include the following steps. First, the at least oneflexibility offer from at least one flexible unit (e.g. flexible system130 in FIG. 1) and the at least one flexibility request from at leastone uncertain unit (e.g. uncertain system 120 in FIG. 1) are ordered.The ordering can be performed based on submission time or based on aprice in the at least one flexibility offer. Then, the matchingconditions for flexibility offers and flexibility requests are checked.A contract between matched buyers of flexibility and providers offlexibility is then set up. A routing table between matched buyers offlexibility and providers of flexibility, where the table defines arealization of uncertain electricity use of the buyer of flexibility isalso set up. The table is then transmitted to the at least one flexibleunit.

FIG. 5 illustrates a process timeline 500, according to an embodiment ofthe present invention. An uncertain unit 530 (e.g. uncertain system 120)submits a flexibility request 570 to the matching engine 510 (e.g.matching engine 110). One or more flexible units 520 (e.g. flexiblesystem 130) submit flexibility offers 571 to the matching engine 510.The matching engine 510 extracts a quantitative measure of uncertaintyfrom the flexibility request 570 and extracts a quantitative measure offlexibility from the flexibility offer 571. In embodiments, the flexibleunits 520 and uncertain units 530 may submit the quantitative measuresdirectly themselves. At 540, the matching engine 510 matches flexibilityrequests 570 and offers 571 according to the procedure described aboveand illustrated in FIG. 4. If a flexibility request 570 can be matchedby flexibility offers 571, contracts 545 are set up between the buyer offlexibility 530 and the one or many providers of flexibility 520. Anotification 572 of acceptance is sent to the buyer of flexibility. Theone or many selected providers of flexibility are also notified andtheir flexibility offers are updated 573 accordingly. The matchingengine 510 sets up a routing table 550. The routing table 550 may be,for example, implemented as a mathematical function that mapsmeasurements 575 of the uncertain electricity consumption or generationto individual control signals 574 that are assigned to the flexiblesystems 520. During time of delivery, the uncertain unit provideselectric energy measurements 575 to the matching engine that then, basedon the routing table 550, assigns control signals 574 to each contractedflexible unit 520. The flexible units also provide electric energymeasurements 576 to the matching platform for the purpose of verifyingex-post if the control signals have been implemented with sufficientaccuracy. A forecast can also be submitted or broadcasted to theflexible units so as to predict likely future energy supply. This dataexchange procedure is repeated for every time step of the delivery timeinterval, as summarized by 578, 579, 580, and 555. After the deliveryinterval, electric energy measurements of the flexible systems 520 arecompared to their control signals 574, 578 in a verification procedure560. Based on the amount of flexibility activated by the measurements575, 579 and the result of the verification procedure 560, an invoice581 is sent to the buyer of flexibility and reimbursements 582 are paidto the providers of flexibility 520.

In addition to the embodiment described in FIG. 5, it is possible to putsome or all of the information exchanged 570-582 on a distributedledger, e.g. a blockchain, and using smart contracts for one or more ofthe steps 540, 545, 550, 555, 560, 565. The distributed ledger will thuskeep one or more multi-party trusted entries of flexibility offers;flexibility requests; baseline information; notification ofacceptance/rejection; routing table; control signals; electric energymeasurements; verification results; invoices and/or payments; and smartcontracts for routing, verification, invoicing, and payments.

As part of the uncertainty-flexibility matching engine, a formalquantitative description of flexibility and uncertainty is required.This invention, in embodiments, uses zonotopes to describe both theflexibility and uncertainty of individual systems over a given finitediscrete-time planning horizon, cf. FIG. 3. The main reasons forchoosing zonotopes are the following. First, many flexible systems facepower and energy constraints that lead to polytopic feasible sets.Zonotopes are a subclass of polytopes and can approximate well thefeasibility polytopes that arise from such types of constraints. Second,zonotopes allow for a parameterized description, described below, thatmakes their aggregation computationally tractable. Third, in contrast togeneral polytopes, it is computationally tractable to check if azonotope is included in the aggregation (the Minkowski sum) of a set ofother zonotopes. In embodiments, checking these inclusion constraints iscrucial to the matching engine.

A zonotope is defined as the set Z(G,c,β):={x∈R^(n):x=c+Gβ,−β≤β≤β}. Itis completely determined by the generator matrix G that contains thegenerator vectors as columns, the zonotope center c, and the symmetricbounds β on the generators.

Let N(G) denote the matrix that contains as rows all the normal vectorsof all possible facets of the zonotope generated by the generator matrixG.

Denote a zonotopic flexibility request by Z_(r)(G,c_(r),β _(r)).

Denote a zonotopic flexibility offer as Z_(j)(G,c_(j),β _(j)).

There exist different matching conditions that determine whether a givenflexibility request can be matched by the set of available flexibilityoffers. In case the flexibility offers can only be matched entirely(integral), the matching condition is

∀S⊆Ω:Z _(r)⊆⊕_(jϵS) Z _(j),

where Ω:={1, . . . , J}, with J denoting the number of availableflexibility offers. The symbol ⊕ denotes the Minkowski sum.

In case the flexibility offers can be matched fractionally, the matchingcondition is ∀S⊆Ω:Z_(r)⊆⊕_(jϵS){circumflex over (Z)}_(j), {circumflexover (Z)}₁⊆Z_(j), where Ω:={1, . . . , J}, with J denoting the number ofavailable flexibility offers.

Inclusion constraints of the form Z_(r)⊆⊕_(jϵS)Z_(j) are equivalent tochecking the following set of inequalities:

$0 \geq {{{{N(G)}\left( {c_{r} - {\sum\limits_{j \in S}\; c_{j}}} \right)}} + {{{{N(G)}G}}{\left( {{\overset{\_}{\beta}}_{r} - {\sum\limits_{j \in S}{\overset{\_}{\beta}}_{j}}} \right).}}}$

Note that checking the above inclusion condition for general polytopicsets is not trivial and computationally expensive.

As an example, consider a wind power plant and a population of plug-inelectric vehicles. The electric energy produced by the wind turbine canbe forecast to some degree but will always be subject to uncertainty.Under the assumption that there is balance responsibility, the windpower plant operator has a strong incentive to make sure that all theenergy produced can be sold, including unforeseen deviations from theforecast. For this reason, the wind power uncertainty is captured by astochastic model and a zonotope is computed that includes 98% of allpossible wind power realizations. Because the wind power plant operatorwishes to hedge against this uncertainty, the zonotope is submitted as aflexibility request to the matching engine. On the other hand, there isa fleet of plug-in electric vehicles that exhibit flexibility in when tocharge their batteries. However, there are constraints on the minimumand maximum energy content and the charging rate. The fleet operatorwould like to exploit this flexibility by submitting it as a zonotopicflexibility offer to the matching engine. If a matching can be foundbetween the flexibility requested by the wind farm and the flexibilityprovided by the fleet of vehicles, a contract is set up that ensuresthat any potential power trajectory generated by the wind farm will beconsumed by the fleet of electric vehicles. The operator of the vehiclefleet is reimbursed for the flexibility provided. The wind farm operatorhas to pay for the received flexibility but is not affected by any winduncertainty anymore.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice.

The computer readable storage medium may be, for example, but is notlimited to, an electronic storage device, a magnetic storage device, anoptical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers, and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

While the foregoing written description of the invention enables one ofordinary skill to make and use what is considered presently to be thebest mode thereof, those of ordinary skill will understand andappreciate the existence of alternatives, adaptations, variations,combinations, and equivalents of the specific embodiment, method, andexamples herein. Those skilled in the art will appreciate that thewithin disclosures are exemplary only and that various modifications maybe made within the scope of the present invention. In addition, while aparticular feature of the teachings may have been disclosed with respectto only one of several implementations, such feature may be combinedwith one or more other features of the other implementations as may bedesired and advantageous for any given or particular function.Furthermore, to the extent that the terms “including”, “includes”,“having”, “has”, “with”, or variants thereof are used in either thedetailed description and the claims, such terms are intended to beinclusive in a manner similar to the term “comprising.”

Other embodiments of the teachings will be apparent to those skilled inthe art from consideration of the specification and practice of theteachings disclosed herein. The invention should therefore not belimited by the described embodiment, method, and examples, but by allembodiments and methods within the scope and spirit of the invention.Accordingly, the present invention is not limited to the specificembodiments as illustrated herein, but is only limited by the followingclaims.

What is claimed is:
 1. A smart grid energy system comprising: a matchingengine operatively connected to the at least one electric energygenerator and the at least one electric load over a computercommunication network and programmed to: receive, over the computercommunication network, a quantitative measure of uncertainty from thegenerator, wherein the generator comprises an uncertain rate of energygeneration; receive, over the computer communication network, aquantitative measure of flexibility from the electric load, wherein theload comprises a flexible rate of energy consumption; generate atime-dependent control signal wherein the control signal is based on azonotope mapping using the quantitative measure of uncertainty and thequantitative measure of flexibility; and transmit the time-dependentcontrol signal to the load to modify the rate of energy consumption. 2.The system of claim 1, wherein the at least one generator is selectedfrom the group consisting of a solar generator and a wind turbinegenerator.
 3. The system of claim 1, wherein the at least one load isselected from the group consisting of an electric heater and an electricvehicle charger.
 4. An apparatus for the coordination of electric energyproduction and consumption configured to communicate with at least oneuncertain unit and an at least one flexible unit via a computercommunication network, the apparatus comprising at least one processor;and at least one memory including computer program code, the at leastone memory and the computer program code configured to, with the atleast one processor, cause the apparatus to at least: receive at leastone flexibility offer from the at least one flexible energy unit,wherein the flexible energy unit is configured to produce energy orconsume energy with a flexible rate; receive at least one flexibilityrequest from the at least one uncertain energy unit, wherein theuncertain energy unit is configured to produce energy or consume energywith an uncertain rate; extract a quantitative measure of uncertaintyfrom each of the at least one flexibility request; extract aquantitative measure of flexibility from each of the at least oneflexibility offer; and generate a time-dependent control signal whereinthe control signal is based on a mapping using the quantitative measureof uncertainty and the quantitative measure of flexibility; and transmitthe time-dependent control signal to the at least one flexible energyunit to modify a rate of energy production or consumption.
 5. Theapparatus of claim 4, wherein the quantitative measure of flexibility isgenerated using zonotopes.
 6. The apparatus of claim 4, wherein thequantitative measure of uncertainty is generated using zonotopes.
 7. Theapparatus of claim 4, wherein at least one uncertain unit is selectedfrom the group consisting of a solar generator and a wind turbinegenerator.
 8. The apparatus of claim 4, wherein at least one flexibleunit is selected from the group consisting of an electric heater and anelectric vehicle charger.
 9. The apparatus of claim 8, wherein thematching engine is further programmed to compute an electric energyforecast of the at least one uncertain unit and broadcast the forecastto the at least one flexible unit.
 10. The apparatus of claim 4, whereinthe matching engine is further configured to transmitting at least onecontrol signal value for an at least one time interval of a deliveryperiod to the at least one flexible unit based on the at least oneassignment.
 11. The apparatus of claim 4, wherein the matching engine isfurther configured to generate an invoice based on the at least oneassignment.
 12. The apparatus of claim 11, wherein the matching enginetransmits a reimbursement to the at least one flexible unit, wherein thereimbursement is based on the quantitative measure of flexibility andthe at least one assignment.
 13. A method of matching uncertainty inenergy production and/or consumption with flexibility in energyproduction and/or consumption, the method comprising: receiving at leastone flexibility offer from at least one flexible energy unit, whereinthe flexible energy unit is configured to generate energy or consumeenergy; receiving at least one flexibility request from at least oneuncertain energy unit, wherein the uncertain energy unit is configuredto generate energy or consume energy; clearing the at least oneflexibility offer and at least one flexibility request; performing anassignment of potential realizations of the uncertain electricitygeneration and/or consumption to corresponding control signals for theelectric energy generation and/or consumption of the at least oneflexible energy unit. receiving at least one electric energy measurementfor a first at least one interval of a delivery period from the at leastone uncertain energy unit; and transmitting at least one control signalvalue for a second at least one time interval of the delivery period tothe at least one flexible energy unit based on the assignment.
 14. Themethod of claim 13, wherein the first at least one interval and thesecond at least one interval correspond to the same time interval. 15.The method of claim 13, further comprising: receiving at least oneelectric energy measurement for a third at least one interval of thedelivery period from the at least one flexible energy unit.
 16. Themethod of claim 15, wherein the first at least one interval and thethird at least one interval correspond to the same time interval. 17.The method of claim 13, further comprising: computing an electric energyforecast and broadcasting the forecast to the at least one flexibleenergy unit so as to predict likely future energy supply.
 18. The methodof claim 13, wherein clearing the flexibility offers and requestscomprises: ordering the at least one flexibility offer from at least oneflexible unit and the at least one flexibility request from at least oneuncertain unit; checking the matching conditions for flexibility offersand flexibility requests; setting up a contract between matched buyersof flexibility and providers of flexibility; setting up a routing tablebetween matched buyers of flexibility and providers of flexibility,wherein the table defines a realization of uncertain electricity use ofthe buyer of flexibility; and transmitting the table to the at least oneflexible unit.
 19. The method of claim 18, wherein ordering is performedbased on submission time.
 20. The method of claim 18, wherein orderingis performed based on a price in the at least one flexibility offer.